Apr
7
Data Licensing: Who Owns the Customer?
Filed Under B2B, Big Data, Blog, data analytics, Financial services, Industry Analysis, internet, Publishing, Reed Elsevier, Search, semantic web, Thomson, Uncategorized, Workflow | Leave a Comment
Three years ago industry commentators in B2B began what has become a parrot-cry – “Look at the workflow!” – and I admit to being more guilty than most. All of a sudden we were looking at compelling applications where publishers/information providers/content companies were discovering that they had data which really did facilitate decision-making or in other ways enable corporate workflows to function more productively, more effectively, cheaper – and quicker. And so, from payroll to procurement, from risk management to assured compliance, we have seen a wonderful rash of data-rich applications, with more to come as machine learning and AI sharpens the cutting edge of what we can do, and the formula subtly alters from “data as content injected into workflow adds value to workflow systems software” to “workflow systems software selects and licenses third party data as content to support software-driven solutions”.
Time to take stock? I think so. I still see liens who will always believe that their content is a more valuable part of the mix than anyone’s system software. I work with B2B players who passionately believe that they should be fully integrated as users of software and content, and who produce a good deal of software themselves, but I work with very few companies who combine long workflow systems software – the sort that goes from the beginning of a process to the end – with having all of the data content needed to fuel the system and satisfy all of the decision point needs on the way. I recall with great pleasure the IP Manager system built by Thomson Reuters IP (now Clarivate Analytics) to support pharma patent lawyers in managing the workflow of new patent activity, where the huge resources of the company fired up the decision process on claims and infringement. And then, at Lexis Nexis Risk, the purchase of ChoicePoint in a company that built its own Hadoop-derived database systems gave opportunities to roll out decision-making systems for US domestic insurers, using its own data with federal and state data readily available under public licensing schemes.
But you notice that these examples are both very large enterprises and a few years old. Today I find fewer dramatic examples of people doing both, and more and more examples of the systems software and the data coming together independently. I had this in mind when looking at the deal which Thomson Reuters and SAP announced two weeks ago. This is undoubtedly a great deal for both parties, since using the Thomson Reuters World Check database to put some real teeth into the SAP Business Partner Screening service employs the market leading data source of PEPs and other folks we mustn’t trade with into the filtering systems of one of the enterprise software majors. I am sure that the royalties will be a high margin delight, and the customers very happy, but those customers are SAP customers, I presume. And Thomson Reuters here are driving one whole element of the SAP service business, So who “owns” the end customer – SAP because the service can only be used by a SAP licensed user? Or do Thomson Reuters have an implicit “ownership” – once SAP’s clients are into this service it will be very hard to change data source , especially in an instance where there is no better one available. But SAP’s client is still only indirectly Thomson Reuters customer, and would only become one if Thomson Reuters decided to build a service that emulated the SAP workflow, or the SAP client decided to go back to using a less sophisticated Thomson – driven enquiry service.
And then my worries were exacerbated by a really interesting conversation with Aravo Solutions (Aravo.com). I would describe this company as a “lurker” – a seventeen year old start-up only now coming into its own time. Being so far in front of the game usually results in extinction, but in this case it has produced an exciting player writing custom and modular workflow software and applying it mostly in fintech markets. And at every stage licensing in best of breed content to supply its functionalities with content from which solutions can be derived. In light of this its licensing partners are unsurprising: amongst them are Accuity (RBI), Dow Jones, D&B, Kompany, Lexis Nexis, Arachnys and Thomson Reuters. Powerful and valuable companies all, but none of them owning the end-user relationship with Aravo’s clients, who include GE, Unilever etc etc.
I would not argue for a moment that you cannot run a rapid growth, high margin business on data licensing. And look at the rapidly failing B2B magazine markets, once the heartland of the sector. They owned the customer, in that they had a direct subscription relationship with him, but they did not have a relationship with him, they did not know he was changing his nature until it was too late, and they continued to send formatted print and online products to him long after the point of relevance was lost. My point simply is that if your new business model is based on being a third party in a licensing relationship, how do you know what is working and what is not? Is your ability to innovate this limited by your software partners understanding of what is happening. And as the complexity of Big Data subject to AI and machine learning grows greater can your partners control your margins as well while you still have to re-invest in more data enrichment to keep your place in the market?
Being the data content partner is not a bed of licensing roses. Things are changing really fast now. Some bigger players can migrate to full service offerings. Others will buy Aravo’s peers and seek niche dominance. But for very many smaller B2B players who have firmly implanted themselves as data suppliers a very uncomfortable situation is developing. They may not be able to own customer relationships or data access pricing. The new position is called Powerlessness.
Feb
20
Innovation is History
Filed Under B2B, Big Data, Blog, data analytics, Education, eLearning, internet, Publishing, Search, semantic web, STM, Uncategorized, Workflow | Leave a Comment
Innovation happens when you recognize it, not when people invent something. Innovation is a state of mind, not a process of will. Innovation cannot be switched on or off like a light. Innovation is not about making things anew, and then making the new as unchangeable as the old it replaced. Innovation is about looking behind you to measure the tide and the speed of flow. Innovation is knowing when to leap in and swim boldly, knowing that stopping swimming means sinking. Innovation has nothing at all to do with the concept I find described everyday in information companies: “we need some younger managers in here to innovate, then we will take the best of their ideas and go with them”. “We have set up a group to go away and do innovation and then we will see if they come up with anything”. “Our innovators are very smart but have no idea of how important the cash cow is to the company and how important it is that we do not compete with ourselves, so we have taken up the best of their ideas and used them to freshen up the existing services”.
After weeks of working with companies that can talk change but not implement it the spirits can flag. But then, like last week I have a space when every door I push open seems to exude innovation. And it is not the perk of the young or the monopoly of garage dwellers in Southern California. Innovation spreads right across the age and gender divides. It is a cast of mind, almost a type of intelligence. Last week I met two real innovators, both of whom were deeply dissatisfied by the difficulty our industry, both information marketplaces and enterprises at large, have in handling change. I would guess they were 30 years apart in age, and their ideas of innovation were radically different, but both were temperamentally discontented by the thought of leaving the status quo unruffled.
Rather than embarrass the innovators who gave me such a filip, let me describe the innovations. E-Qual (http://www.e-qualcompetence.co.uk) is a competency environment. Created initially for the oil industry, it is a way of getting all the relevant information in one place in order to form judgements about whether employees have the background knowledge, the formal learning, the experience on the job, the continuing development activity and anything else they need to be judged as “competent”. In many ways, competency is the shoe that has not yet dropped in the compliance marketplace. Yet what is it about innovation that means that no one in forestry would look at what works in oil and gas, or no one in light engineering would look at how things are done in pharma. And the information players in vertical sectors are just as blinkered. Small wonder that innovation and scale are real problems.
The other innovation I encountered was Wizdom.ai, a child of the team that incubated Colwiz (www.wizdom.ai). Here we. Are in a whole sector – academic research and scholarly communication – but this is one with an almost theological loathing for “not invented here a look at this Claim” continuously updating with billions of data points. Gain powerful insights about the past, present and future with the most comprehensive knowledge graph covering the entire universe of research.
50K organizations
235 countries
2.7B facts
700M citations
289M concept mappings
$700B research funding
78M publications
50M authors
28M affiliations
60K journals
150TB data
Using cutting edge machine learning algorithms, wizdom.ai continuously generates analytics about the scientific developments that are the harbingers of our future world to progress research in the right direction, further and faster.”
A huge amount of data and some large claims, yet whatever happens here we should note that this is the first time someone has walked through the front door of the problem – finding what scholarship is best of breed, worth funding and most likely to have real impact – and said simply “let’s start by putting all the salient data in one place and then see what our best analytics can do”. While I am sure that in those analytics there is great innovation, the dramatic change here for me is a hallmark of innovation – simplicity of approach. The jury is out on whether, beyond its existing case studies and great graphics, this service will produce the insights claimed for it – but if it does it will comprehensively alter the field of vision of academics, funders, researchers in industry, publishers, and government. A big data solution in this sector at this point could be as influential as the foundation, by the truly innovative Eugene Garfield, of ISI and the impact factor. As I left their Oxford offices the most frequent thought in my head was “why hasn’t a publisher invested and acquired this yet!”
Which returns us to the beginning – no one recognises innovation until it has happened and is history – and too late.
« go back — keep looking »